Uncertainty Quantification and Global Sensitivity Analysis for Radio Wave Propagation in Evaporation Duct.
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| Title: | Uncertainty Quantification and Global Sensitivity Analysis for Radio Wave Propagation in Evaporation Duct. |
|---|---|
| Authors: | Li, Mingjian1 (AUTHOR), Liu, Liguo1 (AUTHOR) 1309021015@nue.edu.cn |
| Source: | Remote Sensing. Jun2026, Vol. 18 Issue 11, p1808. 24p. |
| Subjects: | Radio wave propagation, Kriging, Measurement uncertainty (Statistics), Technological complexity, Polynomial chaos, Sensitivity analysis, Reduced-order models |
| Abstract: | Highlights: What are the main findings? Kriging outperforms PCE (Polynomial Chaos Expansion) and PC-Kriging (Polynomial-Chaos Kriging) by capturing rapid multimode oscillations in evaporation ducts. Kriging error falls as normalized frequency V rises, confirming its advantage for complex modal fields. What are the implications of the main findings? Duct height dominates short-range uncertainty; refractivity gradient gains importance at longer ranges. The link between surrogate performance and modal complexity (V) guides physics-based metamodel selection. Accurate prediction of radio wave propagation in evaporation ducts is critical for radar systems but faces significant environmental uncertainties. This study presents an uncertainty quantification and global sensitivity analysis framework comparing three surrogate models: Polynomial Chaos Expansion, Ordinary Kriging, and Polynomial-Chaos Kriging. Using a parabolic equation solver, we quantify how five parameters—mean duct height, duct height slope, potential refractivity gradient, frequency, and root mean square (RMS) wave height—affect propagation loss. We assess predictive accuracy, perform Sobol-based sensitivity analysis, and explore how surrogate performance relates to the normalized frequency V, a parameter characterizing modal complexity. Results show that Kriging consistently outperforms the others: its local interpolation capability proves essential for capturing rapid spatial oscillations caused by multimode interference. We observe a statistically significant negative correlation between Kriging's prediction error and V, suggesting that its local interpolation becomes increasingly advantageous as the modal complexity of the field (quantified by V) increases. This provides a physically interpretable, though not yet predictive, link between surrogate model choice and the underlying propagation physics. Sensitivity analysis reveals that mean duct height dominates uncertainty at short-to-medium ranges, while the potential refractivity gradient becomes increasingly influential at longer ranges. RMS wave height exhibits localized effects near multipath nulls, particularly at higher frequencies. These findings provide quantitative guidance for prioritizing environmental measurements and offer a physically interpretable basis for surrogate model selection in evaporation duct problems. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 194587029 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Uncertainty Quantification and Global Sensitivity Analysis for Radio Wave Propagation in Evaporation Duct. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Li%2C+Mingjian%22">Li, Mingjian</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Liguo%22">Liu, Liguo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> 1309021015@nue.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Jun2026, Vol. 18 Issue 11, p1808. 24p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Radio+wave+propagation%22">Radio wave propagation</searchLink><br /><searchLink fieldCode="DE" term="%22Kriging%22">Kriging</searchLink><br /><searchLink fieldCode="DE" term="%22Measurement+uncertainty+%28Statistics%29%22">Measurement uncertainty (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Technological+complexity%22">Technological complexity</searchLink><br /><searchLink fieldCode="DE" term="%22Polynomial+chaos%22">Polynomial chaos</searchLink><br /><searchLink fieldCode="DE" term="%22Sensitivity+analysis%22">Sensitivity analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Reduced-order+models%22">Reduced-order models</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Highlights: What are the main findings? Kriging outperforms PCE (Polynomial Chaos Expansion) and PC-Kriging (Polynomial-Chaos Kriging) by capturing rapid multimode oscillations in evaporation ducts. Kriging error falls as normalized frequency V rises, confirming its advantage for complex modal fields. What are the implications of the main findings? Duct height dominates short-range uncertainty; refractivity gradient gains importance at longer ranges. The link between surrogate performance and modal complexity (V) guides physics-based metamodel selection. Accurate prediction of radio wave propagation in evaporation ducts is critical for radar systems but faces significant environmental uncertainties. This study presents an uncertainty quantification and global sensitivity analysis framework comparing three surrogate models: Polynomial Chaos Expansion, Ordinary Kriging, and Polynomial-Chaos Kriging. Using a parabolic equation solver, we quantify how five parameters—mean duct height, duct height slope, potential refractivity gradient, frequency, and root mean square (RMS) wave height—affect propagation loss. We assess predictive accuracy, perform Sobol-based sensitivity analysis, and explore how surrogate performance relates to the normalized frequency V, a parameter characterizing modal complexity. Results show that Kriging consistently outperforms the others: its local interpolation capability proves essential for capturing rapid spatial oscillations caused by multimode interference. We observe a statistically significant negative correlation between Kriging's prediction error and V, suggesting that its local interpolation becomes increasingly advantageous as the modal complexity of the field (quantified by V) increases. This provides a physically interpretable, though not yet predictive, link between surrogate model choice and the underlying propagation physics. Sensitivity analysis reveals that mean duct height dominates uncertainty at short-to-medium ranges, while the potential refractivity gradient becomes increasingly influential at longer ranges. RMS wave height exhibits localized effects near multipath nulls, particularly at higher frequencies. These findings provide quantitative guidance for prioritizing environmental measurements and offer a physically interpretable basis for surrogate model selection in evaporation duct problems. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs18111808 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 24 StartPage: 1808 Subjects: – SubjectFull: Radio wave propagation Type: general – SubjectFull: Kriging Type: general – SubjectFull: Measurement uncertainty (Statistics) Type: general – SubjectFull: Technological complexity Type: general – SubjectFull: Polynomial chaos Type: general – SubjectFull: Sensitivity analysis Type: general – SubjectFull: Reduced-order models Type: general Titles: – TitleFull: Uncertainty Quantification and Global Sensitivity Analysis for Radio Wave Propagation in Evaporation Duct. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Li, Mingjian – PersonEntity: Name: NameFull: Liu, Liguo IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 18 – Type: issue Value: 11 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
